mlsanityData to 14 Oct 2026

Battling Hateful Content in Indic Languages HASOC '21

arXiv 2110.12780 ↗First posted 25 Oct 2021cs.CLcited by 1

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Abstract (arXiv)

The extensive rise in consumption of online social media (OSMs) by a large number of people poses a critical problem of curbing the spread of hateful content on these platforms. With the growing usage of OSMs in multiple languages, the task of detecting and characterizing hate becomes more complex. The subtle variations of code-mixed texts along with switching scripts only add to the complexity. This paper presents a solution for the HASOC 2021 Multilingual Twitter Hate-Speech Detection challenge by team PreCog IIIT Hyderabad. We adopt a multilingual transformer based approach and describe our architecture for all 6 subtasks as part of the challenge. Out of the 6 teams that participated in all the subtasks, our submissions rank 3rd overall.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 13 of its 27 references that are in the map. First posted on arXiv 25 Oct 2021.

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13 of 27 references.

References · 13

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  12. 2021Cross-lingual Offensive Language Identification for Low Resource Languages: The Case of Marathicited by 28
1 more
  1. 2021Multilingual Offensive Language Identification for Low-resource Languagescited by 22

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  1. 2025Cyberbullying Detection in Hinglish Text Using MURIL and Explainable AIcited by 0